python 3.x - Pandas Label Duplicates -


given following data frame:

import pandas pd d=pd.dataframe({'label':[1,2,2,2,3,4,4],                'values':[3,5,7,2,5,8,3]}) d     label   values 0     1       3 1     2       5 2     2       7 3     2       2 4     3       5 5     4       8 6     4       3

i know how count unique values this:

d['dup']=d.groupby('label')['label'].transform('count')

which results in:

    label   values  dup 0     1     3       1 1     2     5       3 2     2     7       3 3     2     2       3 4     3     5       1 5     4     8       2 6     4     3       2

but column have following values: 1 if there 1 unique row per label column, 2 if there duplicates , row in question first of such, , 0 if row duplicate of original. this:

    label   values  dup  status 0     1     3       1     1 1     2     5       3     2 2     2     7       3     0 3     2     2       3     0 4     3     5       1     1 5     4     8       2     2 6     4     3       2     0

thanks in advance!

i think can use loc condition created function duplicated:

d['status'] = 2 d.loc[d.dup == 1, 'status'] = 1 d.loc[d.label.duplicated(), 'status'] = 0  print (d)     label  values  dup  status 0      1       3    1       1 1      2       5    3       2 2      2       7    3       0 3      2       2    3       0 4      3       5    1       1 5      4       8    2       2 6      4       3    2       0

or double numpy.where:

d['status1'] = np.where(d.dup == 1, 1,                np.where(d.label.duplicated(), 0, 2))  print (d)      label  values  dup  status  status1 0      1       3    1       1        1 1      2       5    3       2        2 2      2       7    3       0        0 3      2       2    3       0        0 4      3       5    1       1        1 5      4       8    2       2        2 6      4       3    2       0        0

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